Triple
T2566809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberto Alomar |
E57369
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Roberto |
E26746
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Roberto | Statement: [Roberto Alomar, givenName, Roberto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberto Context triple: [Roberto Alomar, givenName, Roberto]
-
A.
Roberto
chosen
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
B.
Riccardo
Riccardo is an Italian given name, equivalent to Richard in English.
-
C.
Leonardo Bravo
Leonardo Bravo was a prominent insurgent leader in Mexico’s War of Independence, known for his role alongside José María Morelos in key campaigns against Spanish royalist forces.
-
D.
Ernesto
Ernesto is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
E.
Emilio
Emilio is a masculine given name of Spanish and Italian origin, borne by various notable figures including military leaders, artists, and politicians.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3602ed08190aad0f9c7ac577eb0 |
completed | March 7, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6565e05081909dc12aa3240de5f2 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:48 p.m.